AI systems

Organizations are increasingly adopting EnterpriseDB's EDB Postgres AI platform due to a rising demand for enhanced control over data in AI systems, particularly in sectors like banking, insurance, retail, and trading. Research from MIT Technology Review Insights indicates that prioritizing AI and data sovereignty significantly predicts success in AI initiatives, with such organizations achieving five times the return on investment. In South Korea, the Industrial Bank of Korea migrated 15 core systems to EDB Postgres AI, citing significant reductions in licensing costs compared to Oracle and improved scalability for future AI services. Shinhan EZ Insurance transitioned its core system to the public cloud using EDB, overcoming challenges related to legacy database licensing and emphasizing the importance of operational stability. Beyond finance, companies like MNTN, Euronext FX, and Kyobo Book Centre have adopted the platform to reduce vendor reliance, manage data workloads, and enhance compliance control. MNTN uses EDB for large-scale analytical processing, Euronext FX has implemented it across four data centers, and Kyobo Book Centre migrated from a costly data warehouse to the EDB solution. A common trend among these deployments is the use of a single Postgres-based platform for transactional processing, analytics, and AI tasks, reflecting an industry initiative to simplify operations and reduce costs. Hensley noted the critical convergence of AI systems with operational data, as AI agents operate against live data in high-volume workflows, highlighting the drawbacks of using separate platforms for transactions and analytics. EnterpriseDB has also received industry accolades for its data management and contributions to the open-source community, reinforcing its market position.